Related papers: Computing support for advanced medical data analys…
A survey of available techniques in hardware to reduce energy consumption
The area of online machine learning in big data streams covers algorithms that are (1) distributed and (2) work from data streams with only a limited possibility to store past data. The first requirement mostly concerns software…
In this paper, we review data mining approaches for health applications. Our focus is on hardware-centric approaches. Modern computers consist of multiple processors, each equipped with multiple cores, each with a set of arithmetic/logical…
Computer hardware costs are the limiting factor in producing highly accurate radiation dose calculations on convenient time scales. Because of this, large-scale, full Monte Carlo simulations and other resource intensive algorithms are often…
The speed and the versatility of today's computers open up new opportunities to simulate complex biological systems. Here we review a computational approach recently proposed by us to model large tumor cell populations and spheroids, and we…
The reproducibility of scientific research has become a point of critical concern. We argue that openness and transparency are critical for reproducibility, and we outline an ecosystem for open and transparent science that has emerged…
Deep learning has been recently applied to a multitude of computer vision and medical image analysis problems. Although recent research efforts have improved the state of the art, most of the methods cannot be easily accessed, compared or…
Recent advances in types and extent of medical imaging technologies has led to proliferation of multimodal quantitative imaging data in cancer. Quantitative medical imaging data refer to numerical representations derived from medical…
In our former works we have made serious efforts to improve the performance of medical image analysis methods with using ensemble-based systems. In this paper, we present a novel hardware-based solution for the efficient adoption of our…
The rapid deployment of Internet of Things (IoT) applications leads to massive data that need to be processed. These IoT applications have specific communication requirements on latency and bandwidth, and present new features on their…
Digital image analysis has made a big advance in many areas of enterprise applications including medicine, industry, and entertainment by assisting the extraction of semantic information from digital images. However, its large computational…
Medical imaging plays a vital role in modern diagnostics; however, interpreting high-resolution radiological data remains time-consuming and susceptible to variability among clinicians. Traditional image processing techniques often lack the…
The proliferation of sensor technologies and advancements in data collection methods have enabled the accumulation of very large amounts of data. Increasingly, these datasets are considered for scientific research. However, the design of…
Emerging technologies that generate a huge amount of data such as the Internet of Things (IoT) services need latency aware computing platforms to support time-critical applications. Due to the on-demand services and scalability features of…
Medical imaging is crucial in modern clinics to guide the diagnosis and treatment of diseases. Medical image reconstruction is one of the most fundamental and important components of medical imaging, whose major objective is to acquire…
The ever-increasing growth in the number of connected smart devices and various Internet of Things (IoT) verticals is leading to a crucial challenge of handling massive amount of raw data generated from distributed IoT systems and providing…
High-performance computing (HPC) is essential for tackling complex computational problems across various domains. As the scale and complexity of HPC applications continue to grow, the need for scalable systems and software architectures…
Recent years have seen a huge development in spatial modelling and prediction methodology, driven by the increased availability of remote-sensing data and the reduced cost of distributed-processing technology. It is well known that…
Currently, it is urgent to ensure QoS in distributed computing systems. This became especially important to the development and spread of cloud services. Big data structures become heavily distributed. Necessary to consider the…
Image-based algorithmic software segmentation is an increasingly important topic in many medical fields. Algorithmic segmentation is used for medical three-dimensional visualization, diagnosis or treatment support, especially in complex…